Particle swarm optimization and differential evolution for base station placement with multi-objective requirements

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Pereira, Marciel Barros
Orientador(a): Cavalcanti, Francisco Rodrigo Porto
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Teleinformática
Planejamento de redes celulares
Otimização heurística
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/13374
Resumo: The infrastructure expansion planning in cellular networks, so called Base Station Placement (BSP) problem, is a challenging task that must consider a large set of aspects, and which cannot be expressed as a linear optimization function. The BSP is known to be a NP-hard problem unable to be solved by any deterministic method. Based on some fundamental assumptions of Long Term Evolution - Advanced (LTE-A) networks, this work proceeds to investigate the use of two methods for BSP optimization task: the Particle Swarm Optimization (PSO) and the Differential Evolution (DE), which were adapted for placement of many new network nodes simultaneously. The optimization process follows two multi-objective functions used as fitness criteria for measuring the performance of each node and of the network. The optimization process is performed in three scenarios where one of them presents actual data collected from a real city. For each scenario, the fitness performance of both methods as well as the optimized points found by each technique are presented
id UFC-7_63faa5ff2cfab3837cebe21c951aa09f
oai_identifier_str oai:repositorio.ufc.br:riufc/13374
network_acronym_str UFC-7
network_name_str Repositório Institucional da Universidade Federal do Ceará (UFC)
repository_id_str
spelling Pereira, Marciel BarrosMaciel, Tarcísio FerreiraCavalcanti, Francisco Rodrigo Porto2015-10-09T14:45:26Z2015-10-09T14:45:26Z2015PEREIRA, M. B. Particle swarm optimization and differential evolution for base station placement with multi-objective requirements. 2015. 72 f. Dissertação (Mestrado em Engenharia de Teleinformática) – Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2015.http://www.repositorio.ufc.br/handle/riufc/13374The infrastructure expansion planning in cellular networks, so called Base Station Placement (BSP) problem, is a challenging task that must consider a large set of aspects, and which cannot be expressed as a linear optimization function. The BSP is known to be a NP-hard problem unable to be solved by any deterministic method. Based on some fundamental assumptions of Long Term Evolution - Advanced (LTE-A) networks, this work proceeds to investigate the use of two methods for BSP optimization task: the Particle Swarm Optimization (PSO) and the Differential Evolution (DE), which were adapted for placement of many new network nodes simultaneously. The optimization process follows two multi-objective functions used as fitness criteria for measuring the performance of each node and of the network. The optimization process is performed in three scenarios where one of them presents actual data collected from a real city. For each scenario, the fitness performance of both methods as well as the optimized points found by each technique are presentedO planejamento de expansão de infraestrutura em redes celulares é uma desafio que exige considerar diversos aspectos que não podem ser separados em uma função de otimização linear. Tal problema de posicionamento de estações base é conhecido por ser do tipo NP-hard, que não pode ser resolvido por qualquer método determinístico. Assumindo características básicas da tecnologia Long Term Evolution (LTE)-Advanced (LTE-A), este trabalho procede à investigação do uso de dois métodos para otimização de posicionamento de estações base: Otimização por Enxame de Partículas – Particle Swarm Optimization (PSO) – e Evolução Diferencial – Differential Evolution (DE) – adaptados para posicionamento de múltiplas estações base simultaneamente. O processo de otimização é orientado por dois tipos de funções custo com multiobjetivos, que medem o desempenho dos novos nós individualmente e de toda a rede coletivamente. A otimização é realizada em três cenários, dos quais um deles apresenta dados reais coletados de uma cidade. Para cada cenário, são exibidos o desempenho dos dois algoritmos em termos da melhoria na função objetivo e os pontos encontrados no processo de otimização por cada uma das técnicasTeleinformáticaPlanejamento de redes celularesOtimização heurísticaParticle swarm optimization and differential evolution for base station placement with multi-objective requirementsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessORIGINAL2015_dis_mbpereira.pdf2015_dis_mbpereira.pdfapplication/pdf3666612http://repositorio.ufc.br/bitstream/riufc/13374/1/2015_dis_mbpereira.pdfbc2466a863d5e64d596e5667f3ef5426MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81786http://repositorio.ufc.br/bitstream/riufc/13374/2/license.txt8c4401d3d14722a7ca2d07c782a1aab3MD52riufc/133742020-08-24 12:04:52.106oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2020-08-24T15:04:52Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
title Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
spellingShingle Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
Pereira, Marciel Barros
Teleinformática
Planejamento de redes celulares
Otimização heurística
title_short Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
title_full Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
title_fullStr Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
title_full_unstemmed Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
title_sort Particle swarm optimization and differential evolution for base station placement with multi-objective requirements
author Pereira, Marciel Barros
author_facet Pereira, Marciel Barros
author_role author
dc.contributor.co-advisor.none.fl_str_mv Maciel, Tarcísio Ferreira
dc.contributor.author.fl_str_mv Pereira, Marciel Barros
dc.contributor.advisor1.fl_str_mv Cavalcanti, Francisco Rodrigo Porto
contributor_str_mv Cavalcanti, Francisco Rodrigo Porto
dc.subject.por.fl_str_mv Teleinformática
Planejamento de redes celulares
Otimização heurística
topic Teleinformática
Planejamento de redes celulares
Otimização heurística
description The infrastructure expansion planning in cellular networks, so called Base Station Placement (BSP) problem, is a challenging task that must consider a large set of aspects, and which cannot be expressed as a linear optimization function. The BSP is known to be a NP-hard problem unable to be solved by any deterministic method. Based on some fundamental assumptions of Long Term Evolution - Advanced (LTE-A) networks, this work proceeds to investigate the use of two methods for BSP optimization task: the Particle Swarm Optimization (PSO) and the Differential Evolution (DE), which were adapted for placement of many new network nodes simultaneously. The optimization process follows two multi-objective functions used as fitness criteria for measuring the performance of each node and of the network. The optimization process is performed in three scenarios where one of them presents actual data collected from a real city. For each scenario, the fitness performance of both methods as well as the optimized points found by each technique are presented
publishDate 2015
dc.date.accessioned.fl_str_mv 2015-10-09T14:45:26Z
dc.date.available.fl_str_mv 2015-10-09T14:45:26Z
dc.date.issued.fl_str_mv 2015
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv PEREIRA, M. B. Particle swarm optimization and differential evolution for base station placement with multi-objective requirements. 2015. 72 f. Dissertação (Mestrado em Engenharia de Teleinformática) – Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2015.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufc.br/handle/riufc/13374
identifier_str_mv PEREIRA, M. B. Particle swarm optimization and differential evolution for base station placement with multi-objective requirements. 2015. 72 f. Dissertação (Mestrado em Engenharia de Teleinformática) – Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2015.
url http://www.repositorio.ufc.br/handle/riufc/13374
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
bitstream.url.fl_str_mv http://repositorio.ufc.br/bitstream/riufc/13374/1/2015_dis_mbpereira.pdf
http://repositorio.ufc.br/bitstream/riufc/13374/2/license.txt
bitstream.checksum.fl_str_mv bc2466a863d5e64d596e5667f3ef5426
8c4401d3d14722a7ca2d07c782a1aab3
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
_version_ 1847792982544089088

Registros relacionados